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--- |
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license: apache-2.0 |
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base_model: openai/whisper-tiny |
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tags: |
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- generated_from_trainer |
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datasets: |
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- PolyAI/minds14 |
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metrics: |
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- wer |
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model-index: |
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- name: whisper-tiny-en |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: minds14 |
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type: minds14 |
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config: en-US |
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split: train |
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args: en-US |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.2883917775090689 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# whisper-tiny-en |
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7626 |
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- Wer Ortho: 0.2891 |
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- Wer: 0.2884 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- training_steps: 4000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:---------:|:------:| |
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| 0.0005 | 35.71 | 500 | 0.6319 | 0.2684 | 0.2684 | |
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| 0.0002 | 71.43 | 1000 | 0.6820 | 0.2709 | 0.2709 | |
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| 0.0001 | 107.14 | 1500 | 0.7092 | 0.2740 | 0.2739 | |
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| 0.0001 | 142.86 | 2000 | 0.7275 | 0.2854 | 0.2848 | |
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| 0.0001 | 178.57 | 2500 | 0.7423 | 0.2885 | 0.2878 | |
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| 0.0 | 214.29 | 3000 | 0.7531 | 0.2898 | 0.2890 | |
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| 0.0 | 250.0 | 3500 | 0.7604 | 0.2898 | 0.2890 | |
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| 0.0 | 285.71 | 4000 | 0.7626 | 0.2891 | 0.2884 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
